Whole-genome analysis of de novo somatic point mutations reveals novel mutational biomarkers in pancreatic cancer

Amin Ghareyazi, Amir Mohseni, Hamed Dashti, Amin Beheshti, Abdollah Dehzangi, Hamid R. Rabiee, Hamid Alinejad-Rokny

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


It is now known that at least 10% of samples with pancreatic cancers (PC) contain a causative mutation in the known susceptibility genes, suggesting the importance of identifying cancer-associated genes that carry the causative mutations in high-risk individuals for early detection of PC. In this study, we develop a statistical pipeline using a new concept, called gene-motif, that utilizes both mutated genes and mutational processes to identify 4211 3-nucleotide PC-associated gene-motifs within 203 significantly mutated genes in PC. Using these gene-motifs as distinguishable features for pancreatic cancer subtyping results in identifying five PC subtypes with distinguishable phenotypes and genotypes. Our comprehensive biological characterization reveals that these PC subtypes are associated with different molecular mechanisms including unique cancer related signaling pathways, in which for most of the subtypes targeted treatment options are currently available. Some of the pathways we identified in all five PC subtypes, including cell cycle and the Axon guidance pathway are frequently seen and mutated in cancer. We also identified Protein kinase C, EGFR (epidermal growth factor receptor) signaling pathway and P53 signaling pathways as potential targets for treatment of the PC subtypes. Altogether, our results uncover the importance of considering both the mutation type and mutated genes in the identification of cancer subtypes and biomarkers.

Original languageEnglish (US)
Article number4376
Issue number17
StatePublished - Sep 1 2021

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


  • Cancer subtype identification
  • Genotype and phenotype characterization
  • Pancreatic cancer
  • Personalized medicine
  • Somatic point mutations
  • Therapeutic targets


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